Systems and methods for using curvatures to analyze facial and body features

ABSTRACT

Systems and methods of providing an attractiveness analysis are disclosed. In some embodiments, an electronic analysis platform is configured to obtain image data and curvature data to provide an attractiveness analysis to a user via a physical interface. Curvature data could comprise any data indicative of a curvature of a physical feature or a depiction thereof, including shadow data and pixilation data.

This application is a divisional of U.S. application Ser. No. 13/607067,filed on Sep. 7, 2012, which claims the benefit of priority to U.S.Provisional Application No. 61/532,837, filed on Sep. 9, 2011. This andall other extrinsic materials discussed herein are incorporated byreference in their entirety. Where a definition or use of a term in anincorporated reference is inconsistent or contrary to the definition ofthat term provided herein, the definition of that term provided hereinapplies and the definition of that term in the reference does not apply.

FIELD OF THE INVENTION

The field of the invention is facial and body attractiveness analysis.

BACKGROUND

The following background discussion includes information that may beuseful in understanding the present invention. It is not an admissionthat any of the information provided herein is prior art or relevant tothe presently claimed invention, or that any publication specifically orimplicitly referenced is prior art.

Beauty care specialists, physicians, and others have long analyzed somephysical features in order to identify items of attractiveness as wellas to determine how to improve a person's attractiveness. Variousarticles present the results of such analysis. These include “Anatomy of‘A Beautiful Face & Smile’,” by Patnaik, et al, J. Anat. Soc. India52(1) 74-80 (2003); “Beauty Can be Explained by Proportions,” by Bass,John W., available athttp://www.realself.com/article/beauty-explained-proportions; and “TheFacial Proportions of Beautiful People,” available athttp://majorityrights.com/weblog/comments//the_facial_proportions_of_beautiful_people.

Based on the various factors that have been thought to determineattractiveness over the years, many others have attempted to providebeauty analysis to users based on images. For example, US PatentApplication Publication No. 2008/0004109 to Kanarat describes a gamingsystem that provides a celebrity match and facial attractiveness scorebased upon how similar that person's face is to a celebrity, and basedon the size and position of facial features. US Patent ApplicationPublication No. 2007/0047761 to Wasilunas analyzes facial symmetry, hairgrowth patterns and spatial data to provide beauty advice to a user.

Kanarat and Wasilunas, however, do not appear to focus on curvatures ofa person's features, and instead look at the size and positions offeatures, a comparison of a user's face to celebrity faces, or facialsymmetry, hair growth patterns and spatial data, which to theApplicant's knowledge, are not accurate indicators of beauty, in and ofthemselves.

U.S. Pat. No. 7,634,103 to Rubinstenn teaches using a 3-D facial imageto provide beauty product suggestions to a user. However, Rubinstennalso fails to focus on curvature to provide accurate and individualizedattractiveness scores or analysis.

One of the current inventor's own books, The Palmer Code (April 2009),describes manual methods of analyzing attractiveness of human faces, andcalculating attractiveness scores. As disclosed in the prior art,however, The Palmer Code, also fails to analyze curvatures to determineattractiveness.

U.S. Pat. No. 8,194,093 to Perlman does use facial curvatures as part ofan analysis, but that use is only with respect to determining facialmovements rather than attractiveness.

The Anaface website, http://www.anaface.com/, claims to provide facialbeauty analysis to users based upon photographs. There again, however,Anaface appears to base its “analysis” on facial symmetry and the lengthand width of certain features, without considering curvatures. (Seee.g., http://greyviremia.livejournal.com/44780.html).

Thus, there is still a need for improved systems and methods thatanalyze facial or body curvatures in assessing attractiveness scores.

Unless the context dictates the contrary, all ranges set forth hereinshould be interpreted as being inclusive of their endpoints, andopen-ended ranges should be interpreted to include commerciallypractical values. Similarly, all lists of values should be considered asinclusive of intermediate values unless the context indicates thecontrary.

SUMMARY OF THE INVENTION

The inventive subject matter provides apparatus, systems and methods inwhich an electronic analysis platform is configured to receive imagedata, obtain curvature data from the image data, and provide a user withan attractiveness score based at least partially on the curvature data.The curvature data could comprise, for example, shadow or shading data,a degree of curvature, a degree of shadowing, a pixilation analysis, orany combination thereof.

The curvature data could be obtained through any known method, includingfor example, analysis of a 3-D image, gradation of pixels, colordensity, luminance contrast, surface triangulation, cross patch, partialderivative technique, gray-scale image conversion and analysis, RGBimage conversion and analysis, and so forth. For example, where thefeature is skin and the image is a grayscale image, a curvature datacould be extracted from image data by determining the ratio of darkerpixels to lighter pixels, the darkness or lightness or each pixel, andthe location of darker pixels relative to lighter pixels.

As used herein, the term “attractiveness score” is used very broadly toinclude, for example, a score representing attractiveness, beauty,sexiness, desirableness, or suitability for a particular activity (e.g.,a sport).

From a user perspective, the user (1) takes, uploads or sends an image(e.g., a photograph or video) to an electronic analysis platform, and(2) obtains an attractiveness score, via a physical user interface.Contemplated user interfaces could be provided via a display of a userdevice, including for example, a mobile telephone, a desktop computer, alaptop computer, a game having a display and a camera, or any otherdevice capable of sending or receiving graphics, texts or audio.

From the perspective of the electronic analysis platform, image data isreceived, an attractiveness score is obtained based at least in part onimage data and curvature data, and the attractiveness score is sent to auser interface.

The electronic analysis platform can be configured as a service thatcould be provided over a wired or wireless communications network. Theplatform or service can advantageously be implemented as one or moresoftware modules executable by at least one processing unit (e.g.,processor or processing core). In some embodiments, the electronicanalysis platform can comprise a computer program configured to access adatabase (e.g., a database storing image data and correspondingattractiveness scores or analysis data), or a second platform, server orservice.

Contemplated image data can comprise a depiction of one or more physicalfeatures of a person, including an entire face or body. As used herein,the term “physical feature” is used very broadly to include for example,(1) an eyebrow, a pair of eyebrows, an eye, a pair of eyes, a nose, amouth, a lip, a check, a forehead, an ear, a pair of ears, or any otherfacial feature, or (2) a waist, a chest, a pair of arms, a pair ofshoulders, a back, a buttocks, a pair of legs, or any other bodilyfeature. It is also contemplated that physical features sometimesincludes an area of skin surrounding a facial feature, e.g., an eye andthe area of skin surrounding the eye.

Where a depiction of more than one physical feature composes the imagedata, it is contemplated that the analysis platform could additionallyobtain a symmetry analysis, or a spatial analysis, between two or moreof the features or curvatures.

The electronic analysis platform, and/or a module accessible by theplatform, could convert the received image data, using existingtechnologies (e.g., Adobe™, ArcSoft™, etc.) into a 3-D, grayscale, orother image data representation in order to allow for a more detailedcurvature or other analysis data.

Various objects, features, aspects and advantages of the inventivesubject matter will become more apparent from the following detaileddescription of preferred embodiments, along with the accompanyingdrawing figures in which like numerals represent like components.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a schematic of a system according to the inventive subjectmatter.

FIG. 2 is a schematic of a grayscale photograph showing four featuresfor analysis.

FIG. 3 is a schematic of a photograph showing various areas of spatialanalysis.

FIG. 4 is a schematic of a comparison of pixilation in two photographs.

FIG. 5 is a schematic of sample pre-scored attractiveness scores basedin part on curvatures.

DETAILED DESCRIPTION

It should be noted that while the following description is drawn tocomputer/server based systems, various alternative configurations arealso deemed suitable and may employ various computing devices includingservers, interfaces, systems, databases, agents, peers, engines,controllers, or other types of computing devices operating individuallyor collectively. One should appreciate the computing devices comprise aprocessor configured to execute software instructions stored on atangible, non-transitory computer readable storage medium (e.g., harddrive, solid state drive, RAM, flash, ROM, etc.). The softwareinstructions preferably configure the computing device to provide theroles, responsibilities, or other functionality as discussed below withrespect to the disclosed apparatus. In especially preferred embodiments,the various servers, systems, databases, or interfaces exchange datausing standardized protocols or algorithms, possibly based on HTTP,HTTPS, AES, public-private key exchanges, web service APIs, knownfinancial transaction protocols, or other electronic informationexchanging methods. Data exchanges preferably are conducted over apacket-switched network, the Internet, LAN, WAN, VPN, or other type ofpacket switched network.

The following discussion provides many example embodiments of theinventive subject matter. Although each embodiment represents a singlecombination of inventive elements, the inventive subject matter isconsidered to include all possible combinations of the disclosedelements. Thus if one embodiment comprises elements A, B, and C, and asecond embodiment comprises elements B and D, then the inventive subjectmatter is also considered to include other remaining combinations of A,B, C, or D, even if not explicitly disclosed.

FIG. 1 shows one embodiment of a system of the inventive subject matter.In FIG. 1, a first user interface (e.g., provided by a mobile phone, adesktop computer, a television, a tablet computer, an arcade gamescreen, etc.) 100 transmits image data 130 to analysis platform 120. Theanalysis platform 120 comprises an import module 122 configured toreceive the image data 130. Analysis platform 120 further comprises ananalysis engine 124, which comprises at least one of a curvatureanalysis module 125, a symmetry analysis module 126, and a spatialanalysis module 127, or any other relevant analysis data obtainingmodule. Analysis platform 120 obtains at least one analysis data (e.g.,a curvature data, a symmetry data, a spatial data, etc.) of at least onefeature via analysis engine 124. The analysis data is sent to scoringengine 129, which calculates or otherwise obtains an attractivenessscore using some or all of the analysis data. Once the analysis platform120 obtains an attractiveness score, the score 140 is sent to a seconduser interface. Second interface 110 could be any physical interface,and could be the same as, or different from, the first interface.

Alternatively or in addition to an attractiveness score, it iscontemplated that the analysis platform could obtain and provide arecommendation (e.g., of a beauty product, a procedure, a style, etc.).

In FIG. 1, analysis engine 124 and scoring engine 129 are located withinanalysis platform 120. However, it is contemplated that an analysisengine or scoring engine could alternatively or additionally be locatedexterior to an analysis platform, and configured to exchange data orotherwise communicate with the analysis platform.

In some embodiments, the analysis data could be sent to a person whocalculates an attractiveness score, thereby bypassing the need for ascoring engine. Analysis data obtained from modules 125-127 could begiven the same or different amount of weight in calculating anattractiveness score.

It is contemplated that each analysis data or attractiveness score couldbe determined based on (1) pre-selected standards (e.g., predeterminedscores corresponding to a degree of shading or pre-selected images), (2)an independent analysis (e.g., viewing or analyzing a shadowing patternwithout any comparison), or (3) a combination thereof

As used herein, the term “spatial data” is used broadly to include, forexample, a length, a width, a distance between, a fullness of, a volumeof, or any combination thereof

As used herein, the term “symmetry data” is used broadly to include, forexample, any information (e.g., a mirror image or one side superimposedon another side and compared) that could be beneficial in determininghow symmetrical one side of a feature, a body or a face, is to anotherside.

As used herein, the term “curvature data” is used broadly to include,for example, a degree of curvature, a shadow data, a degree ofshadowing, a gradation of pixilation, a ratio of light to dark pixels ina given area, a length of shading, or any other suitable datarepresentative of a curve.

FIG. 2 shows image data (e.g., a grayscale image) comprising a depictionof various features. In FIG. 2, image data 200 comprises various facialfeatures to be used in an attractiveness analysis. Each of the featuresor depictions thereof could be analyzed using the same data, e.g.curvature data. Alternatively, it is contemplated that some or all ofthe features or depictions thereof could be analyzed using differentanalysis data. For example, (1) first feature 210 (e.g., hair) could beanalyzed for volume data, curve data, fullness data, color data, lengthdata, and style data, (2) second feature 212 (e.g., a nose) could beanalyzed for curvature data based on shadow or pixilation data 218, 220,or 222, a width, a length, a width of the nose compared to a width ofthe face, and a volume data, (3) third feature 214 (e.g., a cheek) couldbe analyzed based on spatial data (as described in FIG. 3), a color, anda position, and (4) fourth feature 216 (e.g., a chin) could be analyzedbased on spatial data, a volume data, a pointiness, a curvature, and aproximity to a mouth.

As used herein, a reference to an analysis of a feature should beinterpreted as encompassing analyzing a feature or analyzing a depictionof a feature. Thus, an analysis data could comprise an analysis of afeature or a depiction of a feature.

An attractiveness score for image data 200 could be calculated usinganalysis data of each of the first through fourth features (210, 212,214, and 216), or using analysis data of only one or some of thefeatures. For analysis data considered in obtaining an attractivenessscore, one item of analysis data could be given more or less weight thananother item of analysis data. For example, in FIG. 2, an attractivenessscore could be obtained using a curvature data of the first feature, aspatial data of the second feature, a spatial and curvature data of thethird feature, and a spatial data of the fourth feature. The amount ofweight given to the first feature could be 10%, while the amount ofweight given to each of the second, third, and fourth features is 30%.Finally, the 30% weight given to the third feature could be divided as20% weight for curvature data and 10% weight for spatial data.

FIG. 3 shows how a spatial analysis could be performed by a spatialanalysis module. In FIG. 3, image data 300 is analyzed by measuring thedistance between eyes 320, a width of the face 330, a length of the face340, and a match-score based on an analysis of an analysis data withrespect to ideal cheek volume indicator 310. Ideal cheek volumeindicator 310 comprises two lines intersecting at a point. While the twointersecting lines could be drawn along any portions of a face, it ispreferred that the first vertical line is drawn through a pupil, and thesecond horizontal line is drawn across a bottom of the nostril (forwomen) or a little bit higher (for men). The point of intersectionindicates where a bottom portion of a cheekbone extends to in an idealor most attractive cheek.

It is contemplated that a high degree of curvature, distance, symmetry,or other measurement could lead to a higher or lower attractivenessscore. For example, while a high degree of curvature could be desirablefor a buttocks, it could be undesirable for an arm. Moreover, a largerlength (e.g., of a face) could be desirable for a taller person, while asmaller length could be desirable for a shorter person.

It is also contemplated that an attractiveness score could be tailoredto what is considered attractive or desirable in a profession or locale.For example, longer arms and legs with a lot of curvature could bedesirable for a female basketball player, while shorter arms and legsand a long torso could be desirable for a female gymnast. With regard tolocale, a rounder face could be desirable in a given city, state orcountry, while a more angular face could be desirable in another.Attractiveness scores could also be dependent on the sex of a person.

In FIG. 4, a comparison of two female chin and neck areas are shown.Here, the attractiveness scores could be determined for each woman basedon a ratio of dark to light pixilation 420 and 440 in and around thosefeatures 410 and 430, respectively. The image on the right received anattractiveness score of 99 because there is a low ratio of dark to lightpixilation. The image on the left received an attractiveness score of 72because of the higher ratio of dark to light pixilation, as well as thelocation of the darker pixels.

While the attractiveness score of FIG. 4 is based on curvature data ofonly two features, it is contemplated that attractiveness scores couldbe based on any analysis data of 1, 5, 10, or even 100 or more features.

In FIG. 5, a predetermined set of attractiveness scores andcorresponding image data stored in a database 500 is shown. The databasecould comprise scores and analysis or image data(s) related toindividual features, a set of features, or an entire body, face orperson. It is contemplated that an analysis platform could obtain ananalysis data or attractiveness score via a comparison of a receivedimage data and one or more database image data and correspondinganalysis data or attractiveness scores.

An attractiveness score could be based on any scale, including forexample, 0-99, A-Z, low to high, below average to above average, acombination thereof, or any other suitable scale. It is alsocontemplated that an attractiveness score could be a categorization(e.g., exotic beauty, classic beauty, etc.) returned to a user interfacebased at least in part on curvature data.

As used herein, the term “obtain” is used very broadly to include, forexample, deriving, recognizing, extracting, sending an item or data toan outside service that derives or recognizes, or even showing the itemor data to a human who enters an analysis or score.

In some embodiments, the numbers expressing quantities of ingredients,properties such as concentration, reaction conditions, and so forth,used to describe and claim certain embodiments of the invention are tobe understood as being modified in some instances by the term “about.”Accordingly, in some embodiments, the numerical parameters set forth inthe written description and attached claims are approximations that canvary depending upon the desired properties sought to be obtained by aparticular embodiment. In some embodiments, the numerical parametersshould be construed in light of the number of reported significantdigits and by applying ordinary rounding techniques. Notwithstandingthat the numerical ranges and parameters setting forth the broad scopeof some embodiments of the invention are approximations, the numericalvalues set forth in the specific examples are reported as precisely aspracticable. The numerical values presented in some embodiments of theinvention may contain certain errors necessarily resulting from thestandard deviation found in their respective testing measurements.

As used in the description herein and throughout the claims that follow,the meaning of “a,” “an,” and “the” includes plural reference unless thecontext clearly dictates otherwise. Also, as used in the descriptionherein, the meaning of “in” includes “in” and “on” unless the contextclearly dictates otherwise.

The recitation of ranges of values herein is merely intended to serve asa shorthand method of referring individually to each separate valuefalling within the range. Unless otherwise indicated herein, eachindividual value is incorporated into the specification as if it wereindividually recited herein. All methods described herein can beperformed in any suitable order unless otherwise indicated herein orotherwise clearly contradicted by context. The use of any and allexamples, or exemplary language (e.g. “such as”) provided with respectto certain embodiments herein is intended merely to better illuminatethe invention and does not pose a limitation on the scope of theinvention otherwise claimed. No language in the specification should beconstrued as indicating any non-claimed element essential to thepractice of the invention.

Groupings of alternative elements or embodiments of the inventiondisclosed herein are not to be construed as limitations. Each groupmember can be referred to and claimed individually or in any combinationwith other members of the group or other elements found herein. One ormore members of a group can be included in, or deleted from, a group forreasons of convenience and/or patentability. When any such inclusion ordeletion occurs, the specification is herein deemed to contain the groupas modified thus fulfilling the written description of all Markushgroups used in the appended claims.

As used herein, and unless the context dictates otherwise, the term“coupled to” is intended to include both direct coupling (in which twoelements that are coupled to each other contact each other) and indirectcoupling (in which at least one additional element is located betweenthe two elements). Therefore, the terms “coupled to” and “coupled with”are used synonymously.

It should be apparent to those skilled in the art that many moremodifications besides those already described are possible withoutdeparting from the inventive concepts herein. The inventive subjectmatter, therefore, is not to be restricted except in the scope of theappended claims. Moreover, in interpreting both the specification andthe claims, all terms should be interpreted in the broadest possiblemanner consistent with the context. In particular, the terms “comprises”and “comprising” should be interpreted as referring to elements,components, or steps in a non-exclusive manner, indicating that thereferenced elements, components, or steps may be present, or utilized,or combined with other elements, components, or steps that are notexpressly referenced. Where the specification claims refers to at leastone of something selected from the group consisting of A, B, C . . . andN, the text should be interpreted as requiring only one element from thegroup, not A plus N, or B plus N, etc.

What is claimed is:
 1. A system for providing an attractiveness score,comprising: a first physical user interface functionally coupled to anelectronic analysis platform; and wherein the analysis platform isconfigured to: receive image data comprising a depiction of a firstphysical feature of a person; obtain curvature data extracted fromshadow data associated with a first physical feature from the imagedata; obtain spatial data comprising at least length and width of thefirst physical feature, and provide to the user, through a second userinterface, an attractiveness score based at least in part on thecurvature data and the spatial data.
 2. The system of claim 1, whereinthe shadow data comprises a degree of shadowing.
 3. The system of claim1, wherein the first physical feature is at least one of an eyebrow, apair of eyebrows, an eye, a pair of eyes, a nose, a mouth, a lip, acheck, a forehead, an ear, and a pair of ears.
 4. The system of claim 1,wherein the first physical feature is at least one of a waist, a chest,a pair of arms, a pair of shoulders, a back, a buttocks, and a pair oflegs.
 5. The system of claim 1, wherein the first user interface isdifferent from the second user interface.
 6. A system for providing anattractiveness score, comprising: a first physical user interfacefunctionally coupled to an electronic analysis platform and wherein theanalysis platform is configured to: receive image data comprising adepiction of a first physical feature of a person; obtain shadow dataassociated with a first curvature of the first physical feature from theimage data and provide to the user, through a second user interface, anattractiveness score based at least in part on the shadow data andwherein the first analysis platform is further configured to receiveimage data comprising a depiction of a second physical feature of theperson, and wherein the analysis platform is further configured toobtain shadow data associated with a second curvature of the secondphysical feature.
 7. The system of claim 6, wherein the attractivenessscore is further based in part on the second shadow data.
 8. A method ofdetermining an attractiveness of a face, comprising: identifying a firstdegree of shadowing associated with a first curvature of the face;identifying a second degree of shadowing associated with a secondcurvature of the face; and calculating an attractiveness score basedupon the first and second degrees of shadowing.
 9. The method of claim8, wherein the attractiveness score is based upon a predeterminedformula.
 10. The method of claim 8, further comprising the step ofproviding the attractiveness score to a user via a physical userinterface.
 11. The method of claim 8, further comprising the step ofidentifying a distance between the first curvature and the secondcurvature relative to a width or a length of the face.
 12. The method ofclaim 8, further comprising the step of identifying a length and a widthof the face.